A methodology for estimation of physical parameters

Systems Analysis Modelling Simulation

Volumn 43, Issue 7, 2003, Pages 925-943

  Trigeassou, Jean Claude ^a   Poinot, Thierry ^a   Moreau, Sandrine ^a  

^a UNIVERSITÉ DE POITIERS   (France)

Author keywords

Continuous time systems; OE identification techniques; Parameters estimation; Prior knowledge parameter sensitivity functions

Indexed keywords

ALGORITHMS; ELECTRICAL ENGINEERING; ERROR ANALYSIS; FUNCTION EVALUATION; LINEAR SYSTEMS; NONLINEAR PROGRAMMING;

CONTINUOUS TIME SYSTEMS; DETERMINISTIC INTERPRETATION; OE IDENTIFICATION TECHNIQUES; PRIOR KNOWLEDGE PARAMETER SENSITIVITY FUNCTIONS;

PARAMETER ESTIMATION;

EID: 33746330395     PISSN: 02329298     EISSN: 10294902     Source Type: Journal    
DOI: 10.1080/0232929021000055460     Document Type: Article

References (19)

1. T. Bohlin and S.F. Graebc (1994). Issues in non-linear stochastic grey-box identification. SYSID'94, 10th IFAC Symposium of System Identification. Copenhagen, Denmark.
2. P. Eykhoff (1974). System Identification, Parameter and State Estimation. Editions Wiley, London.
3. R. Iserman (1993). Fault diagnosis of machines via parameter estimation and knowledge processing-Tutorial paper. Automatica, 29(4), 815-835.
4. T.A. Johansen (1997). On tikhonov reguralization, bias and variance in non-linear system identification. Automatica, 33(3), 441-446.
5. M. Knudsen (1994). A sensitivity approach for estimation of physical parameters. SYSID'94, 10th IFAC Symposium on System Identification. Copenhagen, Denmark.
6. L. Ljung (1987). In: T. Kailath (Ed.), System Identification - Theory for the User. Prentice Hall, Englewood Cliffs, New Jersey.
7. D.W. Marquardt (1963). An algorithm for least-squares estimation of non-linear parameters. J. Soc. Industr. Appl. Math., 11(2), 431-441.
8. S. Moreau (1999). Contribution à la modélisation et à l'estimation paramétrique des machines électriques à sourant alternatif: application au diagnostic. Thèse de Doctorat, Université de Poitiers, Poitiers.
9. V. Peterka (1981). In: P. Eykhoff (Ed.), Bayesian Approach to System Identification. Trends and Progress in System Identification, pp. 239-304. Pergamon, Oxford.
10. J.C. Radix (1984). In: Cepadues (Ed.), Filtrage et lissage statistiques optimaux linéaires. Imprimarie du Sud, Toulouse.
11. J. Richalet, A. Rault and R. Pouliquen (1971). Identification des processus par la méthode du modèle. Gordon and Breach, Paris.
12. A.H. Sayed and T. Kailath (1998). Recursive Least-Squares Adaptive Filters. Digital Signal Processing Handbook, CRC Press, Boca Raton, Florida.
13. A.N. Tikhonov and U.Y. Arsenin (1997). Solutions of Ill-posed Problems. Winston, Washington, D.C.
14. J.C. Trigeassou (1996). Parameter estimation of continuous systems (in french). Summer School: Surveillance des systèmes continues. Grenoble, France.
15. J.C. Trigeassou, T. Poinot and S. Moreau (2000). A methodology for estimation of physical parameters. IMACS 2000, 16th IMACS World Congress on Scientific Compulation, Applied Mathematics and Simulation. Lausanne, Suisse.
16. H.J.A.F. Tulleken (1993). Grey-box modeling and identification using physical knowledge and bayesian techniques. Automatica, 29(2), 285-308.
17. H. Unbehauen and G.P. Rao (1997). Identification of continuous time systems: a tutorial. SYSID'97, 11th IFAC Symposium on System Identification. Japan.
18. E. Walter and L. Pronzato (1997). Identification of Parametric Models from Experimental Data. Communications and Control Engineering Series, Springer.
19. P. Young (1981). Parameter estimation for continuous-time models-A survey. Automatica, 17(1), 23-39.